Model-based identification of TNFα-induced IKKβ-mediated and IκBα-mediated regulation of NFκB signal transduction as a tool to quantify the impact of drug-induced liver injury compounds

An engineered TNFR1-selective human lymphotoxin-alpha mutant delivered by an oncolytic adenovirus for tumor immunotherapy

Lymphotoxin α (LTα) is a soluble factor produced by activated lymphocytes which is cytotoxic to tumor cells. Although a promising candidate in cancer therapy, the application of recombinant LTα has been limited by its instability and toxicity by systemic administration. Secreted LTα interacts with several distinct receptors for its biological activities. Here, we report a TNFR1-selective human LTα mutant (LTα Q107E) with potent antitumor activity. Recombinant LTα Q107E with N-terminal 23 and 27 aa deletion (named LTα Q1 and Q2, respectively) showed selectivity to TNFR1 in both binding and NF-κB pathway activation assays. To test the therapeutic potential, we constructed an oncolytic adenovirus (oAd) harboring LTα Q107E Q2 mutant (named oAdQ2) and assessed the antitumor effect in mouse xenograft models. Intratumoral delivery of oAdQ2 inhibited tumor growth. In addition, oAdQ2 treatment enhanced T cell and IFNγ-positive CD8 T lymphocyte infiltration in a human PBMC reconstituted-SCID mouse xenograft model. This study provides evidence that reengineering of bioactive cytokines with tissue or cell specific properties may potentiate their therapeutic potential of cytokines with multiple receptors.

Basal MET phosphorylation is an indicator of hepatocyte dysregulation in liver disease

Chronic liver diseases are worldwide on the rise. Due to the rapidly increasing incidence, in particular in Western countries, metabolic dysfunction-associated steatotic liver disease (MASLD) is gaining importance as the disease can develop into hepatocellular carcinoma. Lipid accumulation in hepatocytes has been identified as the characteristic structural change in MASLD development, but molecular mechanisms responsible for disease progression remained unresolved. Here, we uncover in primary hepatocytes from a preclinical model fed with a Western diet (WD) an increased basal MET phosphorylation and a strong downregulation of the PI3K-AKT pathway. Dynamic pathway modeling of hepatocyte growth factor (HGF) signal transduction combined with global proteomics identifies that an elevated basal MET phosphorylation rate is the main driver of altered signaling leading to increased proliferation of WD-hepatocytes. Model-adaptation to patient-derived hepatocytes reveal patient-specific variability in basal MET phosphorylation, which correlates with patient outcome after liver surgery. Thus, dysregulated basal MET phosphorylation could be an indicator for the health status of the liver and thereby inform on the risk of a patient to suffer from liver failure after surgery.

Uncovering specific mechanisms across cell types in dynamical models

Ordinary differential equations are frequently employed for mathematical modeling of biological systems. The identification of mechanisms that are specific to certain cell types is crucial for building useful models and to gain insights into the underlying biological processes. Regularization techniques have been proposed and applied to identify mechanisms specific to two cell types, e.g., healthy and cancer cells, including the LASSO (least absolute shrinkage and selection operator). However, when analyzing more than two cell types, these approaches are not consistent, and require the selection of a reference cell type, which can affect the results. To make the regularization approach applicable to identifying cell-type specific mechanisms in any number of cell types, we propose to incorporate the clustered LASSO into the framework of ordinary differential equation modeling by penalizing the pairwise differences of the logarithmized fold-change parameters encoding a specific mechanism in different cell types. The symmetry introduced by this approach renders the results independent of the reference cell type. We discuss the necessary adaptations of state-of-the-art numerical optimization techniques and the process of model selection for this method. We assess the performance with realistic biological models and synthetic data, and demonstrate that it outperforms existing approaches. Finally, we also exemplify its application to published biological models including experimental data, and link the results to independent biological measurements.

Syringic acid and silymarin concurrent administration inhibits sodium valproate-induced liver injury in rats

Sodium valproate (SV) is a well-known anti-epileptic drug, also used to control convulsions, bipolar disorders and migraines. SV has been shown to induce liver toxicity in clinical subjects. Syringic acid (SA), a natural polyphenolic compound has potential antioxidant, anti-inflammatory and several beneficial effects. Therefore, in this study, we evaluated hepatoprotective effect of SA against SV-induced liver injury in rats. Wistar rats were treated with SV orally at a dose of 500 mg/kg, once daily, for 14 days. Another three groups of rats were administered with SV and concurrently treated with SA (40 and 80 mg/kg) and silymarin (SIL) (100 mg/kg) for 14 days. SV administration for 14 days caused significant (p < .001) elevation of liver transaminases and ALP in serum. Liver MDA level was significantly (p < .001) increased with a concomitant decrease (p < .001) in enzymic antioxidants activities in SV administered rats. SV administration also caused the upregulation of proinflammatory markers such as tumor necrosis factor α, c-Jun N-terminal kinase, nuclear factor kappa B, cyclooxygenase-2 and Interleukin 6 expressions in liver tissue. Histopathological studies also revealed the presence of inflammatory cell infiltration and hepatocellular necrosis upon SV administration. At both doses, concurrent administration of SA and SIL significantly (p < .001) inhibited the liver transaminase activities in serum, oxidative stress, and proinflammatory markers expression in liver tissue. Our current results suggest that SA can be a promising herbal drug that can inhibit SV-induced hepatotoxicity when administered together due its potential anti-inflammatory effects.

Deciphering signal transduction networks in the liver by mechanistic mathematical modelling

In health and disease, liver cells are continuously exposed to cytokines and growth factors. While individual signal transduction pathways induced by these factors were studied in great detail, the cellular responses induced by repeated or combined stimulations are complex and less understood. Growth factor receptors on the cell surface of hepatocytes were shown to be regulated by receptor interactions, receptor trafficking and feedback regulation. Here, we exemplify how mechanistic mathematical modelling based on quantitative data can be employed to disentangle these interactions at the molecular level. Crucial is the analysis at a mechanistic level based on quantitative longitudinal data within a mathematical framework. In such multi-layered information, step-wise mathematical modelling using submodules is of advantage, which is fostered by sharing of standardized experimental data and mathematical models. Integration of signal transduction with metabolic regulation in the liver and mechanistic links to translational approaches promise to provide predictive tools for biology and personalized medicine.

Ethnopharmacological impact of Melaleuca rugulosa (Link) Craven leaves extract on liver inflammation

ETHNOPHARMACOLOGICAL RELEVANCE

Melaleuca species have been used by many ethnic communities for the management and treatment of several ailments as hemorrhoids, cough, skin infections, rheumatism, sore throat, pain, inflammation, and digestive system malfunctions. However, the detailed mechanistic pharmacological effect of Melaleuca rugulosa (Link) Craven leaves in the management of liver inflammation has not been yet addressed.

AIM OF THE STUDY

The present study aimed to evaluate the anti-inflammatory, antioxidant, and antiapoptotic capacities of the aqueous methanol extract of M. rugulosa leaves in relevance to their flavonoid content using an appropriate in vivo model.

MATERIALS AND METHODS

The aqueous methanol extract of M. rugulosa leaves was administered to the rats at three non-toxic doses (250, 500, and 1000 mg/kg) for seven days prior to the initiation of liver-injury induced by paracetamol (3 g/kg). Liver enzymes including alanine aminotransferase (ALT), aspartate aminotransferase (AST), and alkaline phosphatase (ALP) were evaluated in serum samples. The oxidative stress markers including reduced glutathione (GSH), malondialdehyde (MDA), and nitric oxide (NO) levels as well as the inflammatory markers such as tumour necrosis factor-alpha (TNF-α) and nuclear factor-kappa B (NF-κB), were assessed in liver homogenate. The results were supported by histopathological and immuno-histochemical studies. The phytochemical investigation of the flavonoid-rich fraction of the aqueous methanol extract was accomplished using different chromatographic and spectroscopic techniques.

RESULTS

The aqueous methanol extract of M. rugulosa leaves showed a powerful hepatoprotective activity evidenced by the significant reduction of MDA and NO levels, as well as increasing GSH and catalase activity. Moreover, the extract exhibited anti-inflammatory and antiapoptotic activities witnessed by decreasing TNF-α, NF-κB, iNOS, p-JNK, caspase-3, BAX, and increasing Bcl-2 levels. Moreover, the pretreatment of rats with all doses of M. rugulosa leaves extract showed a significant decrease in liver weight/body weight (LW/BW) ratio, and total bilirubin induced by paracetamol. On the other hand, the chromatographic separation of the flavonoid-rich fraction afforded twenty known flavonoids namely; iso-orientin (1), orientin (2), isovitexin (3), vitexin (4), quercetin-3-O-β-D-glucuronid methyl ether (5), quercetin-3-O-β-D-mannuronpyranoside (6), isoquercetin (7), quercitrin (8), kaempferol-3-O-β-D-mannuronopyranoside (9), kaempferol-7-O-methyl ether-3-O-β-D-glucopyranoside (10), guaijaverin (11), avicularin (12), kaempferide-3-O-β-D-glucopyranoside (13), astragalin (14), afzelin (15), luteolin (16), apigenin (17), quercetin (18), kaempferol (19), and catechin (20).

CONCLUSION

The aqueous methanol extract of M. rugulosa leaves showed potential hepatoprotective, antioxidant, and anti-inflammatory activities against paracetamol-induced liver inflammation which is correlated at least in part to its considerable phenolic content.

Mapping the dynamics of Nrf2 antioxidant and NFκB inflammatory responses by soft electrophilic chemicals in human liver cells defines the transition from adaptive to adverse responses

A comprehensive understanding of the dynamic activation and crosstalk between different cellular stress response pathways that drive cell adversity is crucial in chemical safety assessment. Various chemicals have electrophilic properties that drive cell injury responses in particular oxidative stress signaling and inflammatory signaling. Here we used bacterial artificial chromosome-based GFP cellular stress reporters with live cell confocal imaging, to systematically monitor the differential modulation of the dynamics of stress pathway activation by six different soft electrophiles: sulforaphane, andrographolide, diethyl maleate, CDDO-Me, ethacrynic acid and tert-butyl hydroquinone. The various soft electrophiles showed differential potency and dynamics of Nrf2 activation and nuclear translocation. These differences in Nrf2 dynamics correlated with distinct activation pattern of Nrf2 downstream targets SRNX1 and HMOX1. All soft electrophiles caused a strong dose dependent suppression of a cytokine-induced NFĸB response represented by suppression of NFĸB nuclear oscillation and inhibition of the downstream target gene activation A20 and ICAM1, which followed the potency of Nrf2 modulation but occurred at higher concentration close to saturation of Nrf2 activation. RNAi-based depletion of RelA resulted in a prolonged presence of Nrf2 in the nucleus after soft electrophile treatment; depletion of Nrf2 caused the induction of NFĸB signaling and activation of its downstream targets A20 and ICAM1. A systematic transcriptome analysis confirmed these effects by soft electrophiles on Nrf2 and NFκB signaling crosstalk in human induced-pluripotent stem cell-derived hepatocyte-like cells. Altogether our data indicate that modulation of Nrf2 by soft electrophiles may have consequences for efficient inflammatory signaling.

Systems approaches to investigate the role of NF-κB signaling in aging

The nuclear factor-κB (NF-κB) signaling pathway is one of the most well-studied pathways related to inflammation, and its involvement in aging has attracted considerable attention. As aging is a complex phenomenon and is the result of a multi-step process, the involvement of the NF-κB pathway in aging remains unclear. To elucidate the role of NF-κB in the regulation of aging, different systems biology approaches have been employed. A multi-omics data-driven approach can be used to interpret and clarify unknown mechanisms but cannot generate mechanistic regulatory structures alone. In contrast, combining this approach with a mathematical modeling approach can identify the mechanistics of the phenomena of interest. The development of single-cell technologies has also helped clarify the heterogeneity of the NF-κB response and underlying mechanisms. Here, we review advances in the understanding of the regulation of aging by NF-κB by focusing on omics approaches, single-cell analysis, and mathematical modeling of the NF-κB network.

Quantitative predictive approaches for Dupuytren disease: a brief review and future perspectives

In this study we review the current state of the art for Dupuytren's disease (DD), while emphasising the need for a better integration of clinical, experimental and quantitative predictive approaches to understand the evolution of the disease and improve current treatments. We start with a brief review of the biology of this disease and current treatment approaches. Then, since certain aspects in the pathogenesis of this disorder have been compared to various biological aspects of wound healing and malignant processes, next we review some in silico (mathematical modelling and simulations) predictive approaches for complex multi-scale biological interactions occurring in wound healing and cancer. We also review the very few in silico approaches for DD, and emphasise the applicability of these approaches to address more biological questions related to this disease. We conclude by proposing new mathematical modelling and computational approaches for DD, which could be used in the absence of animal models to make qualitative and quantitative predictions about the evolution of this disease that could be further tested in vitro.

Transcription factor NF-κB as target for SARS-CoV-2 drug discovery efforts using inflammation-based QSAR screening model

NF-κB is a central regulator of immunity and inflammation. It is suggested that the inflammatory response mediated by SARS-CoV-2 is predominated by NF-κB activation. Thus, NF-κB inhibition is considered a potential therapeutic strategy for COVID-19. The aim of this study was to identify potential anti-inflammation lead molecules that target NF-κB using a quantitative structure-activity relationships (QSAR) model of currently used and investigated anti-inflammatory drugs as the basis for screening. We applied an integrated approach by starting with the inflammation-based QSAR model to screen three libraries containing more than 220,000 drug-like molecules for the purpose of finding potential drugs that target the NF-κB/IκBα p50/p65 (RelA) complex. We also used QSAR models to rule out molecules that were predicted to be toxic. Among screening libraries, 382 molecules were selected as potentially nontoxic and were analyzed further by short and long molecular dynamics (MD) simulations and free energy calculations. We have discovered five hit ligands with highly predicted anti-inflammation activity and nearly no predicted toxicities which had strongly favorable protein-ligand interactions and conformational stability at the binding pocket compared to a known NF-κB inhibitor (procyanidin B2). We propose these hit molecules as potential NF-κB inhibitors which can be further investigated in pre-clinical studies against SARS-CoV-2 and may be used as a scaffold for chemical optimization and drug development efforts.

Integration of temporal single cell cellular stress response activity with logic-ODE modeling reveals activation of ATF4-CHOP axis as a critical predictor of drug-induced liver injury

Drug-induced liver injury (DILI) is the most prevalent adversity encountered in drug development and clinical settings leading to urgent needs to understand the underlying mechanisms. In this study, we have systematically investigated the dynamics of the activation of cellular stress response pathways and cell death outcomes upon exposure of a panel of liver toxicants using live cell imaging of fluorescent reporter cell lines. We established a comprehensive temporal dynamic response profile of a large set of BAC-GFP HepG2 cell lines representing the following components of stress signaling: i) unfolded protein response (UPR) [ATF4, XBP1, BIP and CHOP]; ii) oxidative stress [NRF2, SRXN1, HMOX1]; iii) DNA damage [P53, P21, BTG2, MDM2]; and iv) NF-κB pathway [A20, ICAM1]. We quantified the single cell GFP expression as a surrogate for endogenous protein expression using live cell imaging over > 60 h upon exposure to 14 DILI compounds at multiple concentrations. Using logic-based ordinary differential equation (Logic-ODE), we modelled the dynamic profiles of the different stress responses and extracted specific descriptors potentially predicting the progressive outcomes. We identified the activation of ATF4-CHOP axis of the UPR as the key pathway showing the highest correlation with cell death upon DILI compound perturbation. Knocking down main components of the UPR provided partial protection from compound-induced cytotoxicity, indicating a complex interplay among UPR components as well as other stress pathways. Our results suggest that a systematic analysis of the temporal dynamics of ATF4-CHOP axis activation can support the identification of DILI risk for new candidate drugs.

On Valve Interstitial Cell Signaling: The Link Between Multiscale Mechanics and Mechanobiology

Heart valves function in one of the most mechanically demanding environments in the body to ensure unidirectional blood flow. The resident valve interstitial cells respond to this mechanical environment and maintain the structure and integrity of the heart valve tissues to preserve homeostasis. While the mechanics of organ-tissue-cell heart valve function has progressed, the intracellular signaling network downstream of mechanical stimuli has not been fully elucidated. This has hindered efforts to both understand heart valve mechanobiology and rationally identify drug targets for treating valve disease. In the present work, we review the current literature on VIC mechanobiology and then propose mechanistic mathematical modeling of the mechanically-stimulated VIC signaling response to comprehend the coupling between VIC mechanobiology and valve mechanics.

ATF6 Is a Critical Determinant of CHOP Dynamics during the Unfolded Protein Response

The unfolded protein response (UPR) pathway senses unfolded proteins and regulates proteostasis and cell fate through activity of the transcription factors ATF4, ATF6, and XBP1 within a complex network of three main branches. Here, we investigated contributions of the three branches to UPR activity in single cells using microscopy-based quantification and dynamic modeling. BAC-GFP HepG2 reporter cell lines were exposed to tunicamycin, and activation of various UPR components was monitored for 24 h. We constructed a dynamic model to describe the adaptive UPR signaling network, for which incorporation of all three branches was required to match the data. Our calibrated model suggested that ATF6 shapes the early dynamics of pro-apoptotic CHOP. We confirmed this hypothesis by measurements beyond 24 h, by perturbing single siRNA knockdowns and by ATF6 measurements. Overall, our work indicates that ATF6 is an important regulator of CHOP, which in turn regulates cell fate decisions.

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A mathematical model of the unfolded protein response describes microscopy data

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Integration of modeling and experimental work offers insights into UPR regulation

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ATF6 shapes the early dynamics of the CHOP response

Targeting the NF-κB/IκBα complex via fragment-based E-Pharmacophore virtual screening and binary QSAR models

Nuclear factor-κB (NF-κB) transcription factors represent a conserved family of proteins that regulate not only immune cells, but also heart cells, glial cells and neurons, playing a fundamental role in various cellular processes. Due to its dysregulation in certain cancer types as well as in chronic inflammation and autoimmune diseases, it has recently been appreciated as an important therapeutic target. The aim of this study was to investigate the binding pocket of NF-κB (p50/p65) heterodimer complex in association with NF-κB inhibitor IκBα to identify potent ligands via fragment-based e-pharmacophore screening. The ZINC Clean Fragments (∼2 million) and the Schrodinger's medically relevant Glide fragments library (∼670) were used to create the e-pharmacophore models at the potential binding site which was validated by site mapping. Glide/HTVS docking was conducted followed by re-docking of the top 20% fragments by Glide/SP and Glide/XP protocols. The top-85000 Glide XP-docked fragments were used to generate the e-pharmacophore hypotheses. The Otava small molecule library (∼260000 drug-like molecules) and 85 known NF-κB inhibitors were additionally screened against the derived e-pharmacophore models. The top-1000 high-scored molecules, which were well aligned to the e-pharmacophore models, from the Otava small molecule library, were then docked into the binding pocket. Finally, the selected 88 hit molecules and the 85 known inhibitors were analyzed by the MetaCore/MetaDrug™ platform, which uses developed binary QSAR models for therapeutic activity prediction as well as pharmacokinetic and toxicity profile predictions of screening molecules. Ligand selection criteria led to the refinement of 3 potent hit molecules using molecular dynamics (MD) simulations to better investigate their structural and dynamical profiles. The selected hit molecules had a low toxicity and a significant therapeutic potential for heart failure, antiviral activity, asthma and depression, all conditions in which NF-κB plays a critical role. These hit ligands were also structurally stable at the NF-κB/IκBα complex as per the MD simulations and MM/GBSA analysis. Two of these ligands (Otava IDs: 1426436 and 6248112) showed stronger binding and therefore are hypothesized to be more potent. The identification of new potent NF-κB/IκBα inhibitors may thus present a novel therapy for inflammation-mediated conditions as well as cancer, facilitating more efficient research, and leading the way to future drug development efforts.